Title :
Combination weight fuzzy recognition model and its application in the assessment of water resource renewability
Author :
Ge, Hui ; Huang, Zhenping ; Liu, Kelin ; Li, Jing
Author_Institution :
Coll. of Hydrol. & Water Resources, Hohai Univ., Nanjing, China
Abstract :
This paper applies a combination weight method to scientifically evaluate the renewability of water resources and rationally determine the weight of evaluation indexes. The approach integrates subjective and objective factors, in which the minimum sum of square of deviations is used as objective function, the optimal model is established to determine weight, and fuzzy pattern recognition theory is combined to set up a new model, i.e., the combination weight fuzzy recognition model. This model is used to evaluate the water resources renewability of nine administrative regions along the Yellow River Basin. Evaluation results are compared with findings generated by the other evaluation method. Results show that the water resources of the Yellow River Basin have weak renewability. The proposed evaluation model is more reasonable and feasible.
Keywords :
environmental management; fuzzy set theory; optimisation; pattern recognition; water resources; Yellow River Basin; combination weight fuzzy recognition model; evaluation index; fuzzy pattern recognition theory; objective factors; objective function; optimal model; subjective factors; water resource renewability assessment; Biological system modeling; Gallium nitride; Genetics; combination weight; component; fuzzy recognition; renewability; water resources;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
DOI :
10.1109/ICCASM.2010.5622610